Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

Murphy, Emma F.; Gilmour, Steven G.; Crabbe, M. James C.

doi:10.1016/s0165-022x(02)00183-5

Cited by 18 publications

(32 citation statements)

References 15 publications

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“…The hypothesis was that the negative influence of these two issues could be minimized by using optimal experimental design. Previous studies have reported different approaches to optimize the estimations of enzyme kinetic parameters for simple or complex enzyme systems (Endrenyi and Chan, 1981;Bardsley et al, 1996;Kakkar et al, 2000;Murphy et al, 2003;Yang et al, 2007;Youdim et al, 2010). In addition, for basic information of the compounds' metabolic stability, the use of a single-time-point practice has been shown (Di et al, 2004).…”

Section: Discussionmentioning

confidence: 99%

Optimal Experimental Design for Assessment of Enzyme Kinetics in a Drug Discovery Screening Environment

Sjögren¹,

Nyberg²,

Magnusson³

et al. 2011

Drug Metab Dispos

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ABSTRACT:A penalized expectation of determinant (ED)-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (V max and K m ) was collected from previously reported studies, and every V max /K m pair (n ‫؍‬ 76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min, and starting concentrations (C 0 ) for the incubation between 0.01 and 100 M. The optimization was performed by finding the sample times and C 0 returning the lowest uncertainty (S.E.) of the model parameter estimates. Individual optimal designs, one general optimal design and one, for laboratory practice suitable, pragmatic optimal design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D by using the Michaelis-Menten (MM) equation, and enzyme kinetic parameters were estimated with both MM and a monoexponential decay. OD generated a better result (relative standard error) for 99% of the compounds and an equal or better result [(root mean square error (RMSE)] for 78% of the compounds in estimation of metabolic intrinsic clearance. Furthermore, high-quality estimates (RMSE < 30%) of both V max and K m could be obtained for a considerable number (26%) of the investigated compounds by using the suggested OD. The results presented in this study demonstrate that the output could generally be improved compared with that obtained from the standard approaches used today.

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Section: Discussionmentioning

confidence: 99%

Optimal Experimental Design for Assessment of Enzyme Kinetics in a Drug Discovery Screening Environment

Sjögren¹,

Nyberg²,

Magnusson³

et al. 2011

Drug Metab Dispos

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show abstract

“…OED can also be employed for designing parallel experiments (Galvanin et al, 2007). Only few applications of OED for the design of enzymatic experiments exist (Duggleby and Clarke, 1991;Lindner and Hitzmann, 2006;Murphy et al, 2003). Moreover, these studies mostly focused on simple Michaelis-Menten equations and none of them was used to design optimal experiments in biphasic systems.…”

Section: Optimal Experimental Design and Measurement Techniquesmentioning

confidence: 99%

“…This is not only essential for design, optimization, and control of industrial processes using enzymes, but also in the medical and pharmaceutical research for the prediction of toxic or metabolic effects in the human body. Since incorrectly designed experiments can cause poor parameter estimates, the need for well-designed enzymatic experiments is becoming increasingly recognized in research (Murphy et al, 2003). An optimal design saves resources such as time, money, and materials, and generates parameter estimates with high precision.…”

Section: Optimal Experimental Design For Enzyme Kinetics Of Benzaldehmentioning

confidence: 99%

“…Moreover, possible model variants can be discriminated (Franceschini and Macchietto, 2007Walter and Pronzato, 1990). To date, most studies on experimental design of enzyme kinetics focus on initial rate measurements and are based on qualitative considerations rather than rigorous numerical methods (Alberty, 2008;Murphy et al, 2003). In contrast to this, only few studies apply optimal experimental design (OED) techniques for optimizing progress curve measurements (Duggleby and Clarke, 1991;Lindner and Hitzmann, 2006).…”

Section: Optimal Experimental Design For Enzyme Kinetics Of Benzaldehmentioning

confidence: 99%

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Model-based experimental analysis of enzyme kinetics in aqueous–organic biphasic systems

Zavrel

Schmidt

Michalik

et al. 2007

Journal of Biotechnology

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“…More recently we developed a set of rules and procedures for Bayesian experimental design for enzyme kinetics, starting with a very rough prior K M estimate [8]. It was shown that a number of features of the design, including the substrate range and individual concentrations measured at, greatly a¡ect the success of and error in the subsequent analysis of the data.…”

Section: Introductionmentioning

confidence: 99%

Efficient and cost‐effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

2003

Self Cite

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Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the e⁄ciency and cost-e¡ectiveness by reducing the necessary amount of experiments and data points measured.

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Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

Cited by 18 publications

References 15 publications

Optimal Experimental Design for Assessment of Enzyme Kinetics in a Drug Discovery Screening Environment

Optimal Experimental Design for Assessment of Enzyme Kinetics in a Drug Discovery Screening Environment

Model-based experimental analysis of enzyme kinetics in aqueous–organic biphasic systems

Efficient and cost‐effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

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